1. Statement of the Technical Field
The invention concerns image processing, and more particularly, an image processing method for images having different spatial and spectral resolutions.
2. Description of the Related Art
In the field of remote image sensing, two common types of images include panchromatic imagery and multi-spectral imagery. Panchromatic imagery is imagery that is obtained by a remote sensing device with a sensor designed to detect electromagnetic energy in only one very broad band. This one very broad band typically includes most of the wavelengths of visible light. Panchromatic imagery has the advantage of offering very high spatial resolution. In contrast, multi-spectral imagery is typically created from several narrow spectral bands within the visible light region and the near infrared region. Consequently, a multi-spectral image is generally comprised of two or more image data sets, each created by sensors responsive to different portions of the optical spectrum (e.g., blue, green, red, infrared). Multi-spectral images are advantageous because they contain spectral information which is not available from a similar panchromatic image. However, multi-spectral images typically have a lower spatial resolution as compared to panchromatic images.
It is often desirable to enhance a multi-spectral image with the high resolution of a panchromatic image and vice versa. Typically this process is referred to as “fusing” of the image pair. In general, there are several requirements for successfully accomplishing the fusing process. One requirement is the need for registration of the two images. The registration process involves a determination of where each pixel in the panchromatic image maps to a location in the multi-spectral image. This process must generally be accomplished with great accuracy for best results. For example, it is desirable for each pixel in the pan image to be mapped to the multi-spectral image with an accuracy of less than 0.1 panchromatic pixel radius.
A number of conventional methods exist for registering image pairs. In one method, registration is estimated based on the phase shift in the Fourier domain. That is, one of the images is shifted in the Fourier domain to match the second image. In another method, the sensor model for the acquired images is adjusted to project a small number of match points to a common flat earth. Typically, in such methods, the imaged location is assumed to be static and nearly flat, resulting in a smooth mapping such as an affine or projective transform. In some instances, known topographical information, such as in a digital elevation model (DEM), may be used to adjust the transform. However, such mapping methods can require an extensive amount of computation to match up and align all the pixels in the image pair to be combined.